Study design
This is an open-label pilot study investigating the safety and tolerability of Annona muricata leaf product in people with stage III and IV cancers who are either ineligible for, or who have chosen not to undertake chemotherapeutic treatments. Ethics approval has been granted by Human Research Ethics Committee Bellberry (2022-04-420). The ethics approved protocol has been registered with the Australian New Zealand Clinical Trials Register (ACTRN 12622001288718) and will be conducted in compliance with the SPIRIT statement [10].
Setting and research team
The setting for this study is the Concord Cancer Centre based at Concord Repatriation General Hospital, New South Wales, Australia. The research team includes a hospital oncologist and a clinical pharmacist, who both have extensive experience in herbal medicine cancer clinical trials. The extended research team contribute expertise in the areas of complementary medicines, pharmacology, pharmacy and phytochemistry. Participants will be closely monitored by the clinical trial oncologist.
Investigational product
The study medication selected for this study is a commercially available product listed with The United States Food and Drug Administration (FDA) as Graviola (brand name Swanson Inc.). This product is manufactured in Layton, UST, Inc., a Good Manufacturing Practice (GMP) certified company. The research team have also conducted an independent analysis for quality and safety of the product. This included testing by an Australian National Association of Testing Authorities (NATA) approved laboratory (the Australian Laboratory Services, Smithfield, NSW, Australia) for microbial contaminants prior to use. The trial herbal medicine product was also analysed by the research team for contamination with heavy metals. In addition, quantification of annonacin, one of the most abundant and active compounds was conducted. Cell-line studies were also conducted prior to the study commencement for analysing its cytotoxicity in various cancer cell-lines.
Study Objectives
Primary outcome
The primary outcome of this study will be the safety and tolerability of the Anonna muricata product. The primary outcome will be measured by participants self-reporting of adverse effects experienced and the proportion of participants completing the study. In addition, participants’ safety measurements including carcinoembryonic antigen (CEA), full blood count, liver and renal function will be evaluated. Participants’ cognitive function will also be assessed by conducting the standardised mini-mental state examination (SMMSE) and standard neurological assessment to ensure no neurotoxic effect is experienced.
Secondary outcomes
The secondary outcomes are markers of inflammation, immune function, quality of life and disease status. Inflammatory markers including serum neutrophil-lymphocyte ratio, C-reactive protein and albumin will be measured. These inflammatory markers are associated with cancer prognosis [11–13]. Immune function changes will be measured using flow cytometry to assess changes in CD3, CD4, CD8, CD16/56, CD19 and lymphocyte helper:suppressor ratio. These white blood cells are indirect markers of tumour activity [14]. The ratio of T-cells subsets (CD4 and CD8) and natural killer cells (CD16/56) indicates a pro- or anti-tumour effect [14].
Quality of life of participants will be assessed by conducting the Functional Assessment of Cancer Therapy – General (FACT-G) version 4 and Functional Assessment of Chronic Illness Therapy – Fatigue (FACIT-Fatigue) version 4 questionnaires. Both FACT-G and FACIT-Fatigue have demonstrated reliability and validity and enables the assessment of participants’ quality of life in the previous seven days [15, 16]. The 28-question FACT-G questionnaire comprehensively evaluates the quality of life of participants evaluating physical, social/family, emotional and functional well-being aspects. Each FACT-G questionnaire is accompanied by a set of additional questions specific to a cancer type. Depending on participants’ cancer types, they will be provided with the relevant additional questions specific to their cancer [17]. The 16-question FACIT-Fatigue questionnaire has also been utilised by previous herbal-cancer study as part of quality of life assessment [18].
Disease status will be measured by changes in appropriate biomarkers during standard care such as carcinoembryonic antigen (CEA) and imaging.
Study procedures
Participants and recruitment
Participant recruitment will be conducted at the Concord Cancer Centre at Concord Repatriation General Hospital by a medical oncologist and clinical trials team. Potential participants meeting the eligibility criteria will be approached by a member of the research team to participate in this clinical trial. The target sample size is 24 participants across two dosing levels.
Eligibility
Inclusion criteria include the diagnosis of metastatic or recurrent cancer at stage III or IV; willing and able to undertake the trial treatment and clinical follow-up; aged ≥ 18 years of age; able to understand the English language to give consent and complete questionnaires. Patients who are clinically stable after central nervous system and/or cranial radiation will be included. This is supported by a lack of evidence of progression by CT scan or MRI or on clinical grounds.
Exclusion criteria include participants who are actively undergoing (or intend to receive) chemotherapeutic and/or radiotherapeutic treatments; pregnant or breastfeeding; experience dysphagia; Eastern Cooperative Oncology Group (ECOG) performance status ≥ 3; life expectancy status ≤ 12 weeks; full blood counts with white blood cells < 3.0 × 109/L, absolute neutrophil count < 1.5 × 109/L, platelets < 100 × 109/dL; inadequate hepatic (either aspartate transaminase: ALT > 2.5 × upper limit of normal (ULN), or > 5 × ULN for liver metastatic patient or bilirubin > 1.5 × ULN) and/or renal function (< 50 mL/min/1.73 m2); mucositis (disrupted gastrointestinal integrity); grade 2 or higher peripheral neuropathy toxicity; diagnosis of any major psychiatric or neurodegenerative disorders such as Parkinson’s disease or dementia; other major serious medical illness such as poorly controlled diabetes or cardiovascular disease. Participants will also be excluded if they are concurrently taking other T&CM and unable to cease these medicines two weeks before the trial, already enrolled in other cancer treatment trials, plan to undergo major surgery during study, documented allergy to study treatment.
Intervention
Participants (n = 24) will be allocated to one of two treatment groups, with each group allocated to receive a different dose and commence at different time points as illustrated in Table 1 and Fig. 1. Following the initial 3-week period, each group will be evaluated for safety and tolerability of the allocated dose before continuing for a further three weeks. The trial will run for a total period of 12 weeks for each group.
The rolling recruitment and three weekly assessments will allow for each dose to be evaluated for safety and tolerability prior to commencing the subsequent groups onto a higher dose.
Table 1
Dosage regimen of Annona muricata
Group | 1 | 2 |
n | 12 | 12 |
Dosage regimen | 1 capsule daily | 1 capsule twice daily |
Total daily dose | 530 mg | 1060 mg |
Dose regimen justification
The proposed dose regimen in this study is based on the available information from clinical and animal studies. A previous clinical trial conducted in people with type II diabetes (n = 30) utilised the ethanolic leaf extract of Annona muricata in a daily dose range of 180 to 540 mg. Mild adverse effects were experienced by participants including mild epigastric burn (n = 2) and nausea (n = 4) [19]. Another study conducted in people with colorectal cancer (n = 30) employed a daily dose of 300 mg ethanolic leaf extract of Annona muricata. Adverse effects were reported to be experienced by one participant in this study included anal pain [20].
In toxicological studies, the minimum oral dosage of the ethanolic Annona muricata leaf extract to achieve toxicity in mice was 1000 mg/kg [21]. The calculated oral LD50 of the ethanolic leaf extract in mice is 1670 mg/kg [22]. Our previous systematic review also suggests a favourable safety and tolerability profile in clinical use [21].
The current study utilises an Annona muricata daily dose range from 530 to 1060 mg. The minimum dose (530 mg) is based on the evidence obtained from a previous clinical trial [19]. The incremental increases in doses for each group is to establish safety and tolerability at the lower dose. The highest dose (1060 mg) is based on a case study [4]. The initial dose utilized in the current study is below the human equivalent dose of rat (12.2 mg/kg) [23, 24]. Participants will be closely monitored at 3-week intervals to assess the safety profile of the herb at specified doses.
Demographic and related medical data collection
Demographic and medical information including age, gender, ethnicity, educational level, medical history, cancer diagnosis, cancer stage and previous cancer treatment will be collected at baseline. Concurrent medication, blood glucose, blood pressure, CEA, full blood count, serum creatinine, liver function including gamma glutamyl transferase (GGT), alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP) and bilirubin levels will be recorded at baseline, weeks 3, 6, 9 and week 12. Adherence of Annona muricata capsules will be assessed by participant dosing diary and by counting returned medication as compared to the prescribed dose at the week 6 and week 12. Additional 5 mL of plasma samples will be collected through routine blood sampling and stored frozen for later analyses. These include evaluation of annonacin metabolite and validation of annonacin detection in the blood sample.
Data collection
Samples and data will be collected during visits at baseline, weeks 3, 6, 9 and 12 according to the schedule presented in Table 2. Participants will be requested to keep a participant dosing diary to record any symptoms experienced. One standard tube of blood collected from participants will be frozen for later analysis, including evaluation of annonacin metabolite and validation of annonacin detection in blood sample.
Table 2 Timeline of dosage regimen and data collection
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)
*Tests included in standard care and results data will be analysed
Data Analysis and data presentation
Potential adverse reactions reported by participants will be assessed by employing the Naranjo algorithm to assess causality (definite, probable, possible, doubtful) [25]. Adverse drug reactions will be graded using the National Cancer Institute Common Terminology Criteria for Adverse Events V5 [26].
Data integrity will be maintained by regularly reviewing the data for missing data and errors and any inconsistencies will be resolved. Descriptive statistics will be reported for baseline data including participants’ characteristics. For continuous outcome data including serum neutrophil-lymphocyte ration, C-reactive protein, albumin, CD3, CD4, CD16/56, CD19, lymphocyte helper: suppressor ratio, renal and liver function, linear mixed models will be used to examine changes in outcome measures over time. Dose effects will be examined by fitting dosage group as a factor. If there is evidence of an effect of time, post-hoc independent sample t-test will be conducted to compare the mean at follow-up time-points (week 3, 6, 9 and 12) to baseline. If the continuous data is not normally distributed, non-parametric equivalents tests of the above data will be used. For categorical data, proportion and frequencies will be presented in tables. For binary outcomes including whether renal, liver function, full blood count and CEA falls within or out of the reference range will be assessed by mixed-effect logistic regression.
Statistical data including p-value, 95% confidence interval will be reported. Statistically significant results are considered to have a p-value < 0.05. Data analysis will be conducted using SPSS version 27.0.
Modification of protocol
Any modification of the protocol such as changes in study design will require a formal protocol amendment. These amendments will be discussed among investigators for consensus. Ethical approval will be sought before implementation. Members of the study team, clinicians and participants will be informed of any changes.